Dr Sachinkumar Veerashetty
Professor
| Department of Computer Science and Engineering
Sharnbasva University
Karnataka
Expertise:
Computer Science Theory and Methods
25
Publications
0
Projects
113
Scopus Citations
92
CrossRef
14 Years 11 Months Total Experience
Scopus
113
Citations
6
h-index
CrossRef
92
Citations
5
h-index
Google Scholar
Loading Scholar statistics...
Professional Recognition
No Data Found
There is currently nothing to display here.
Community & Membership
Grievance Redressal Committee (GRC), Sharnbasva University
Member SecretaryAcademic Counil, Sharnbasva University
MemberBoard of Studies, Dept Computer Science and Engg, Sharnbasva University
MemberBoard of Examiner, Dept Computer Science and Engg, Sharnbasva University
MemberThe Institution of Electronics & Telecommunication Engineers (IETE)
FellowInternational Association of Engineers
MemberPersonal Details
Doctor of Philosophy
2019
Guru Nanak Khalsa College, Yamuna Nagar
Master of Technology
2011
Guru Nanak Khalsa College, Yamuna Nagar
Bachelor of Engineering
2009
Guru Nanak Khalsa College, Yamuna Nagar
Professor
Oct 2024 – Present
Sharnbasva University
| Department of Computer Science and Engineering
Associate Professor
Jan 2020 – Oct 2024
Sharnbasva University
| Department of Computer Science and Engineering
Associate Professor
Jan 2015 – Oct 2019
Appa Institute of Engineering & Technology, GULBARGA
| Computer Science and Engineering
Assistant Professor
Jan 2012 – Jan 2015
Appa Institute of Engineering & Technology, GULBARGA
| Computer Science and Engineering
Lecturer
Aug 2011 – Dec 2011
Sharnbasva University
| Department of Computer Science and Engineering
Engineering and Technology
Scholarly Work
No Data Found
There is currently nothing to display here.
DIABETIC RETINOPATHY DETECTION USING MACHINE LEARNING
No Data Found
There is currently nothing to display here.
Scholarly Publications
MCF-UPCN: Modified Conditional Random Field-based Deep Learning Model for Liver Tumor Detection using Computed Tomography Images
Advanced Segmentation and Prediction for Diabetic Retinopathy Detection in Complex Retinal Images
DRFEC-Net: A Framework for Accurate Diabetic Retinopathy Classification
Ultra-High Field Inspired Deep Learning Pipelines for 3T and 7T Level Brain MRI Analysis
Improving Diabetic Retinopathy Fundus Image Quality Using Dynamic Sparse Representation and Dilated Convolutional Networks
Open AccessExplainable Multimodal Deep Learning for MRI-based Brain Disorder Diagnosis
Customized ShuffleNet with Map Reduce Framework for Bigdata Healthcare Monitoring System
Design of rotation, illumination, and scale invariant Gabor texture descriptor for image texture analysis and retrieval
Showing 1 to 8 of 25 publications